Diagnosis of a biological sample with low level of expression of a disease such as cancer (whether due to weak detection signal or a very low concentration of diseased components such as circulating tumor cells (CTCs) in cancer screening) is a challenge in modern medicine. Many diseases with low mortality such as cancer and heart diseases have low level of expression (low level of disease components) which makes detection even more difficult. For example, for late stage cancer patients, the level of CTCs in blood stream is as low as one per billion, making detection extremely difficult. As a result, many diseases such as cancer cannot be easily diagnosed at early stage.
Many serious diseases with high morbidity and mortality, including cancer, are very difficult to diagnose early and accurately. Current disease diagnosis technologies typically rely on macroscopic data and information such as body temperature, blood pressure, and scanned images of the body. To detect serious diseases such as cancer and heart diseases, many of the diagnosis apparatus commonly used today are based on imaging technologies, including x-ray, CT scan, and nuclear magnetic resonance (NMR). While they provide various degrees of usefulness in disease diagnosis, most of them cannot provide accurate, totally safe, and cost-effective diagnosis of such serious diseases as cancer at an early stage. Further, many of the existing diagnosis techniques and related apparatus are invasive and sometimes not readily accessible, especially in remote regions or rural areas.
Even the newly emerged technologies such as those deployed in DNA tests have not been proven effective in diagnosing a wide range of diseases in a rapid, reliable, accurate, and cost-effective manner. In recent years, there have been some efforts in using nano technologies for various biological applications, with most of the work focused on gene mapping and moderate developments in the field of disease detection. For instance, Pantel et al. discussed the use of a MicroEelectroMechanical Systems (MEMS) sensor for detecting cancer cells in blood and bone marrow in vitro (see, e.g., Klaus Pantel et al., Nature Reviews, 2008, 8, 329); Kubena et al. disclose in U.S. Pat. No. 6,922,118 the deployment of MEMS for detecting biological agents; and Weissman et al. disclose in U.S. Pat. No. 6,330,885 utilizing MEMS sensor for detecting accretion of biological matter.
However, to date, most of the above described technologies have been limited to isolated examples for sensing, using systems of relatively simple constructions and large dimensions but often with limited functions, and lack sensitivities and specificities. Further, some existing technologies utilizing nano-particles and biological approaches have the drawbacks of requiring complicated sample preparation procedures (such as using chemical or biological markers), difficulty in data interpretation, and too much reliance on visual and color change as means of diagnosis (which is subjective and of limited resolution), making them unsuitable for early stage disease detection, e.g., for such serious diseases as cancer, and particularly for routine hospital screening and/or regular physical check-up examinations. Some cannot achieve high degree of sensitivity and specificity simultaneously.
These drawbacks call for novel solutions that not only overcome them but also bring improved accuracy, sensitivity, specificity, efficiency, non-invasiveness, practicality, simplicity, and speed in early-stage disease detection at reduced costs.
The existing detection technology and equipment are dominated by single-technology based single purpose equipment with limited disease detection coverage scope, limited functionalities and low efficiency. They are often very extensive, with large foot print (such as NMR, CT, and x-ray machine). They mainly consist of three large groups: (a) imaging-based technology for mid to late stage cancers, (b) bio-marker based technology which offers some sensitivity to specific type of cancer (but for a given bio-marker, it is typically only sensitive to one type or one sub-type of cancer, with relatively low level of specificity), and (c) genomics based detection technology which is relatively insensitive and long processing time.
Because the images are able to identify the disease only when it is in the mid to late stage, the methods and apparatus that heavily depend on imaging-based technologies are not suitable or capable of detecting early-stage diseases, particularly cancer.
Compared with imaging based technologies, bio-marker can detect certain specific cancer at an earlier stage. However, it is a complicated detection technology and process. With a relatively low specificity, it is prone to false alarm in detection. Further, it is narrow in detection scope and applications in terms of cancer types, since typically for a given bio- marker, it is only sensitive to a particular type or sub-type of cancer. As a result, it may not be suited for a general physical check-up (such as annual physical) for cancer screening. It also may not be used alone for cancer detection and it may require additional diagnosis tools for verifications.
Some other techniques may be capable of detecting certain general parameters of cancer, but they cannot distinguish or identify (i.e., determine) the specific type of cancer. In other words, even if those techniques can alert the existing of a cancerous disease, it cannot specify the type of cancer and hence requires additional diagnosis using other detection technologies. Thus, it alone cannot offer a cancer diagnosis solution.
The existing detection technology has various issues including (a) only capable of detecting mid to late stage cancers (particularly CT, X-ray and NMR technologies), (b) high costs (PET-CT, CT, x-ray and NMR), (c) low detection sensitivity to a number of types of cancers and circulating tumor cells (CTCs), (d) some with low specificity (for example, some bio-marker based technologies), and (e) invasive (such as x-ray and NMR). In particular, there is no viable detection technology for early stage disease screening such as cancer screening which can only detect early stage cancer, but also be able to identify which type of cancer. Because early stage disease screening typically deals with low to very low level of disease expression where disease component has a low to very low concentration, and requires a high level of detection sensitivity and specificity, it is highly desirable to have a novel, efficiency, relatively simple, and cost effective separation method to pre-processing the samples to be detected to enhance the level of disease component (e.g., for cancer detection, to increase the concentration of CTCs in the sample before employing detection techniques) for enhanced detection capabilities (such as sensitivity).
There is a need for providing the ability in terms of both general (cancer detection at an early stage) and specific type(s) of cancer. The limitations described above on the currently existing cancer detection technologies show that no currently existing methods and equipments is able to effectively detect simultaneously both general parameters in a biological entity for detecting of cancer and identifying the specific cancer type.
To overcome the above problems, sometimes, it is necessary to concentrate (enhance) the level of the diseased component in the sample to be measured through separation processes. However, many separation processes and technologies are complicated, expensive, or not effective. So far, there is no viable separation process for wide clinical applications to concentrate a one in a billion cancer disease sample to a level which can be easily detected using existing detection methods. Therefore, there exists a critical importance and great demand to innovate and develop a viable, simple, efficient, and cost effective separation method for concentrating a sample from a patient with a low to very low disease expression (low level of disease component concentration) for enhanced detection capability.